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Extracting Spatial Information from Historical Maps

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Release : 2018-11-23
Genre : Computers
Kind : eBook
Book Rating : 926/5 ( reviews)

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Book Synopsis Extracting Spatial Information from Historical Maps by : Benedikt Budig

Download or read book Extracting Spatial Information from Historical Maps written by Benedikt Budig. This book was released on 2018-11-23. Available in PDF, EPUB and Kindle. Book excerpt: Historical maps are fascinating documents and a valuable source of information for scientists of various disciplines. Many of these maps are available as scanned bitmap images, but in order to make them searchable in useful ways, a structured representation of the contained information is desirable. This book deals with the extraction of spatial information from historical maps. This cannot be expected to be solved fully automatically (since it involves difficult semantics), but is also too tedious to be done manually at scale. The methodology used in this book combines the strengths of both computers and humans: it describes efficient algorithms to largely automate information extraction tasks and pairs these algorithms with smart user interactions to handle what is not understood by the algorithm. The effectiveness of this approach is shown for various kinds of spatial documents from the 16th to the early 20th century.

Using Historical Maps in Scientific Studies

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Release : 2019-11-26
Genre : Science
Kind : eBook
Book Rating : 076/5 ( reviews)

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Book Synopsis Using Historical Maps in Scientific Studies by : Yao-Yi Chiang

Download or read book Using Historical Maps in Scientific Studies written by Yao-Yi Chiang. This book was released on 2019-11-26. Available in PDF, EPUB and Kindle. Book excerpt: This book illustrates the first connection between the map user community and the developers of digital map processing technologies by providing several applications, challenges, and best practices in working with historical maps. After the introduction chapter, in this book, Chapter 2 presents a variety of existing applications of historical maps to demonstrate varying needs for processing historical maps in scientific studies (e.g., thousands of historical maps from a map series vs. a few historical maps from various publishers and with different cartographic styles). Chapter 2 also describes case studies introducing typical types of semi-automatic and automatic digital map processing technologies. The case studies showcase the strengths and weaknesses of semi-automatic and automatic approaches by testing them in a symbol recognition task on the same scanned map. Chapter 3 presents the technical challenges and trends in building a map processing, modeling, linking, and publishing framework. The framework will enable querying historical map collections as a unified and structured spatiotemporal source in which individual geographic phenomena (extracted from maps) are modeled (described) with semantic descriptions and linked to other data sources (e.g., DBpedia, a structured version of Wikipedia). Chapter 4 dives into the recent advancement in deep learning technologies and their applications on digital map processing. The chapter reviews existing deep learning models for their capabilities on geographic feature extraction from historical maps and compares different types of training strategies. A comprehensive experiment is described to compare different models and their performance. Historical maps are fascinating to look at and contain valuable retrospective place information difficult to find elsewhere. However, the full potential of historical maps has not been realized because the users of scanned historical maps and the developers of digital map processing technologies are from a wide range of disciplines and often work in silos. Each chapter in this book can be read individually, but the order of chapters in this book helps the reader to first understand the “product requirements” of a successful digital map processing system, then review the existing challenges and technologies, and finally follow the more recent trend of deep learning applications for processing historical maps. The primary audience for this book includes scientists and researchers whose work requires long-term historical geographic data as well as librarians. The secondary audience includes anyone who loves maps!

Document Analysis and Recognition - ICDAR 2023

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Release : 2023-08-18
Genre : Computers
Kind : eBook
Book Rating : 348/5 ( reviews)

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Book Synopsis Document Analysis and Recognition - ICDAR 2023 by : Gernot A. Fink

Download or read book Document Analysis and Recognition - ICDAR 2023 written by Gernot A. Fink. This book was released on 2023-08-18. Available in PDF, EPUB and Kindle. Book excerpt: This six-volume set of LNCS 14187, 14188, 14189, 14190, 14191 and 14192 constitutes the refereed proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR 2021, held in San José, CA, USA, in August 2023. The 53 full papers were carefully reviewed and selected from 316 submissions, and are presented with 101 poster presentations. The papers are organized into the following topical sections: Graphics Recognition, Frontiers in Handwriting Recognition, Document Analysis and Recognition.

Smart Plot Division, Research on the Morphological Evolution of Nanjing South Historic Urban Area and its Plot Redivision since 1949

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Release : 2020-09-15
Genre : Architecture
Kind : eBook
Book Rating : 644/5 ( reviews)

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Book Synopsis Smart Plot Division, Research on the Morphological Evolution of Nanjing South Historic Urban Area and its Plot Redivision since 1949 by : Liu, Peng

Download or read book Smart Plot Division, Research on the Morphological Evolution of Nanjing South Historic Urban Area and its Plot Redivision since 1949 written by Liu, Peng. This book was released on 2020-09-15. Available in PDF, EPUB and Kindle. Book excerpt: Taking Nanjing old south area as an example, this research analyses the changes and problems of the plot division mechanism since 1949 and its impact on urban forms. Changes in the plot division mechanism show that megaplots have been a constant in the ever-changing land development system since 1949, leading to elimination of historic land subdivisions. In this sense, it is necessary to establish a set of smart plot division strategies to promote the restoration of this historic urban area.

Computational Humanities

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Release : 2024-09-24
Genre : Social Science
Kind : eBook
Book Rating : 765/5 ( reviews)

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Book Synopsis Computational Humanities by : Jessica Marie Johnson

Download or read book Computational Humanities written by Jessica Marie Johnson. This book was released on 2024-09-24. Available in PDF, EPUB and Kindle. Book excerpt: The first book to intervene in debates on computation in the digital humanities Bringing together leading experts from across North America and Europe, Computational Humanities redirects debates around computation and humanities digital scholarship from dualistic arguments to nuanced discourse centered around theories of knowledge and power. This volume is organized around four questions: Why or why not pursue computational humanities? How do we engage in computational humanities? What can we study using these methods? Who are the stakeholders? Recent advances in technologies for image and sound processing have expanded computational approaches to cultural forms beyond text, and new forms of data, from listservs and code repositories to tweets and other social media content, have enlivened debates about what counts as digital humanities scholarship. Providing case studies of collaborations between humanities-centered and computation-centered researchers, this volume highlights both opportunities and frictions, showing that data and computation are as much about power, prestige, and precarity as they are about p-values. Contributors: Mark Algee-Hewitt, Stanford U; David Bamman, U of California, Berkeley; Kaspar Beelen, U of London; Peter Bell, Philipps U of Marburg; Tobias Blanke, U of Amsterdam; Julia Damerow, Arizona State U; Quinn Dombrowski, Stanford U; Crystal Nicole Eddins, U of Pittsburgh; Abraham Gibson, U of Texas at San Antonio; Tassie Gniady; Crystal Hall, Bowdoin College; Vanessa M. Holden, U of Kentucky; David Kloster, Indiana U; Manfred D. Laubichler, Arizona State U; Katherine McDonough, Lancaster U; Barbara McGillivray, King’s College London; Megan Meredith-Lobay, Simon Fraser U; Federico Nanni, Alan Turing Institute; Fabian Offert, U of California, Santa Barbara; Hannah Ringler, Illinois Institute of Technology; Roopika Risam, Dartmouth College; Joshua D. Rothman, U of Alabama; Benjamin M. Schmidt; Lisa Tagliaferri, Rutgers U; Jeffrey Tharsen, U of Chicago; Marieke van Erp, Royal Netherlands Academy of Arts and Sciences; Lee Zickel, Case Western Reserve U.

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